A fuzzy-rule-based driving architecture for non-player characters in a car racing game

Videogame-based competitions have been the target of considerable interest among researchers over the past few years since they provide an ideal framework in which to apply soft computing techniques. One of the most popular competitions is the Simulated Car Racing Competition which, thanks to the realism implemented by recent car simulators, provides an excellent test bed for the application of autonomous driving techniques. The present work describes the design and implementation of a car controller able to deal with competitive racing situations. The complete driving architecture consists of six simple modules, each one responsible for a basic aspect of car driving. Three modules use simple functions to control gear shifting, steering movements, and pedal positions. A fourth manages speed control by means of a simple fuzzy system. The other two modules are in charge of (i) adapting the driving behaviour to the presence of other cars, and (ii) implementing a basic 'inter-lap' learning mechanism in order to remember key track segments and adapt the speed accordingly in future laps. The controller was evaluated in two ways. First, in runs without adversaries over several track designs, our controller allowed some of the longest distances to be covered in a set time in comparison with data from other previous controllers, and second, as a participant in the 2009 Simulated Car Racing Competition which it ended up winning.